Smart Footwear Insole for Recognition of Foot Pronation and Supination Using Neural Networks
|Author||Domínguez Morales, Manuel Jesús
Luna Perejón, Francisco
Miró Amarante, María Lourdes
Hernández Velázquez, María Dolores
Sevillano Ramos, José Luis
|Department||Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores
Universidad de Sevilla. Departamento de Tecnología Electrónica
|Abstract||Abnormal foot postures during gait are common sources of pain and pathologies of the
lower limbs. Measurements of foot plantar pressures in both dynamic and static conditions can detect
these abnormal foot postures and ...
Abnormal foot postures during gait are common sources of pain and pathologies of the lower limbs. Measurements of foot plantar pressures in both dynamic and static conditions can detect these abnormal foot postures and prevent possible pathologies. In this work, a plantar pressure measurement system is developed to identify areas with higher or lower pressure load. This system is composed of an embedded system placed in the insole and a user application. The instrumented insole consists of a low-power microcontroller, seven pressure sensors and a low-energy bluetooth module. The user application receives and shows the insole pressure information in real-time and, finally, provides information about the foot posture. In order to identify the different pressure states and obtain the final information of the study with greater accuracy, a Deep Learning neural network system has been integrated into the user application. The neural network can be trained using a stored dataset in order to obtain the classification results in real-time. Results prove that this system provides an accuracy over 90% using a training dataset of 3000+ steps from 6 different users.
|Citation||Domínguez Morales, M.J., Luna Perejón, F., Miró Amarante, M.L., Hernández Velázquez, M.D. y Sevillano Ramos, J.L. (2019). Smart Footwear Insole for Recognition of Foot Pronation and Supination Using Neural Networks. Applied Sciencies, 9 (19)|